{"id":1909148,"url":"https://alion.io/job/hcltech-senioradministrator-data-security-and-compliancepresales","title":"SeniorAdministrator - Data security and compliance,Presales","company":{"id":225,"name":"HCLTech","domain":"hcltech.com","url":"https://alion.io/company/hcltech","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":null},"role":"Solutions","role_family":"Solutions","seniority":null,"employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":["Vijayawada, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Databricks","optional":false},{"name":"Least Privilege","optional":false},{"name":"Python","optional":false},{"name":"ServiceNow","optional":false}],"status":"live","first_seen_at":"2026-10-05T13:59:16Z","employer_posted_date":"2026-10-05","last_verified_at":"2026-10-21T04:21:29Z","board_verified":true,"closed_at":null,"days_open":15,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":15},"description":"Job Summary\nDesign and implement masking policies using Databricks (deterministic, random, shuffling, substitution, key-based, format-preserving), ensuring consistent masking across systems.\nImplement and manage Data Subset strategies (constraint-based, rule-based) and optimize extracts for performance and storage.\nBuild and schedule data flow for end-to-end orchestration (extract, mask, validate, publish), including dependencies, parameters, and notifications.\nPerform post-mask validation (row counts, referential integrity checks, key uniqueness, format checks) and reconcile issues with source/application teams.\nMonitor and troubleshoot the job execution (logs, performance bottlenecks, failures) and drive incident/problem resolution through ServiceNow.\nEnsure compliance with data privacy and audit requirements (least privilege access, evidence capture, approvals, retention/cleanup of test extracts).\nCreate and maintain reusable masking rule libraries, templates, and standardized runbooks to improve repeatability across applications.\nCoordinate releases and stakeholder communication: refresh windows, downtime impacts, sign-offs, and delivery confirmations.\nDesign and build data pipelines using Python to provision test datasets from enterprise sources.\nKey Responsibilities\nDesign and implement masking policies using Databricks (deterministic, random, shuffling, substitution, key-based, format-preserving), ensuring consistent masking across systems.\nImplement and manage Data Subset strategies (constraint-based, rule-based) and optimize extracts for performance and storage.\nBuild and schedule data flow for end-to-end orchestration (extract, mask, validate, publish), including dependencies, parameters, and notifications.\nPerform post-mask validation (row counts, referential integrity checks, key uniqueness, format checks) and reconcile issues with source/application teams.\nMonitor and troubleshoot the job execution (logs, performance bottlenecks, failures) and drive incident/problem resolution through ServiceNow.\nEnsure compliance with data privacy and audit requirements (least privilege access, evidence capture, approvals, retention/cleanup of test extracts).\nCreate and maintain reusable masking rule libraries, templates, and standardized runbooks to improve repeatability across applications.\nCoordinate releases and stakeholder communication: refresh windows, downtime impacts, sign-offs, and delivery confirmations.\nDesign and build data pipelines using Python to provision test datasets from enterprise sources.\nSkill Requirements\nDesign and implement masking policies using Databricks (deterministic, random, shuffling, substitution, key-based, format-preserving), ensuring consistent masking across systems.\nImplement and manage Data Subset strategies (constraint-based, rule-based) and optimize extracts for performance and storage.\nBuild and schedule data flow for end-to-end orchestration (extract, mask, validate, publish), including dependencies, parameters, and notifications.\nPerform post-mask validation (row counts, referential integrity checks, key uniqueness, format checks) and reconcile issues with source/application teams.\nMonitor and troubleshoot the job execution (logs, performance bottlenecks, failures) and drive incident/problem resolution through ServiceNow.\nEnsure compliance with data privacy and audit requirements (least privilege access, evidence capture, approvals, retention/cleanup of test extracts).\nCreate and maintain reusable masking rule libraries, templates, and standardized runbooks to improve repeatability across applications.\nCoordinate releases and stakeholder communication: refresh windows, downtime impacts, sign-offs, and delivery confirmations.\nDesign and build data pipelines using Python to provision test datasets from enterprise sources.\nOther Requirements\nDesign and implement masking policies using Databricks (deterministic, random, shuffling, substitution, key-based, format-preserving), ensuring consistent masking across systems.\nImplement and manage Data Subset strategies (constraint-based, rule-based) and optimize extracts for performance and storage.\nBuild and schedule data flow for end-to-end orchestration (extract, mask, validate, publish), including dependencies, parameters, and notifications.\nPerform post-mask validation (row counts, referential integrity checks, key uniqueness, format checks) and reconcile issues with source/application teams.\nMonitor and troubleshoot the job execution (logs, performance bottlenecks, failures) and drive incident/problem resolution through ServiceNow.\nEnsure compliance with data privacy and audit requirements (least privilege access, evidence capture, approvals, retention/cleanup of test extracts).\nCreate and maintain reusable masking rule libraries, templates, and standardized runbooks to improve repeatability across applications.\nCoordinate releases and stakeholder communication: refresh windows, downtime impacts, sign-offs, and delivery confirmations.\nDesign and build data pipelines using Python to provision test datasets from enterprise sources.","description_format":"text","description_chars":5110,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["IT Consulting & Digital Transformation","IT Outsourcing & Dedicated 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